Why Classifying Teaching Environments Is Essential for Modeling New Teachers

When considering how teaching environments affect teachers, I realized that classification repeatedly appears in my modeling process, suggesting it is a necessary step.

I believe it is.

Why classify? Our mind tends to split complex situations, selecting key or important influencing factors to understand the context—a simplification process. Facing a problem (or the desire to solve one) often means the problem itself is vague; without familiar theory, we rely on our cognition, making classification of influencing factors essential.

Classification is directly linked to finding variables in modeling. It isolates important factors, turning quantifiable elements into variables for model building, and serves as a way to find clues and explore ideas.

Regarding teaching environments, we can categorize them into classroom teaching outcomes (knowledge, process, emotion), teacher‑student relationships, colleague relationships, etc. I would first examine how these elements affect a new teacher, then formulate hypotheses—for example, a novice’s teaching tendency may lie between their initial inclination and that of experienced teachers. With data, statistical modeling is possible; if structural functions are hard to construct, numerical simulation can be used; lacking both, we may hypothesize mechanisms and conduct mechanistic analysis.

Classification also aids pattern recognition based on personal experience. A good classification can inspire connections to related problems, allowing us to apply proven models to solve them.